The specification relates to assessing the quality of nodes in a social network. More specifically, the specification relates to generating weighted clustering coefficients for a social network graph to quantify how tightly interconnected a community is around a node.
In social networks, nodes may be tightly associated with other nodes or groups of nodes. For example, a rock star is followed by lots of fans or a popular school teacher is surrounded by students and parents on a social network. A clustering coefficient has been extensively used to measure the degree to which nodes in a social network cluster together. However, computing the clustering coefficient can be challenging. The computation of the clustering coefficient requires counting the number of triangles in a social network, which can be hard to implement on a large-scale social network graph. Additionally, a systematic study of the clustering coefficient of weighted networks has not yet been undertaken. Current approaches mainly compute the clustering coefficient of an unweighted network, and therefore neglect the intensity of the interaction between nodes that is usually represented with weights on edges of the social network graph and that measures the statistical cohesiveness of the social network.